The accuracy of the timing of maintenance action highly affects the useful life length of the maintained equipment/component, number of failures, number of planned replacements, mean time to repair, maintenance direct costs and consequently production costs. The more accurate the maintenance action timing, the higher the utilization of the component life.
Curative Maintenance (CM) as opposite to Preventive Maintenance (PM) is a generic maintenance policy when there are no countermeasures planned to detect the onset of-, or to prevent-, failure. The related costs (production stops, safety breaches, material and hours) are usually high, but its considered cost-effective in certain cases. The main objectives of using preventive maintenance (PM) are to reduce the number of failures and their economic consequences by performing maintenance actions at a predetermined point of times (age-based or calendar time), regardless of the condition of the equipment/component. The time to perform any form of maintenance action is usually estimated in order to minimize maintenance costs. In order to plan the accurate intervals for PM organizations are in need of decision support systems, historical data.
A Condition-based maintenance (CBM) policy must be based on deterministic and probabilistic models. Data about failure behavior can be obtained via parameters which give direct or indirect information about the actual state of a component. Maintenance decisions, based actual or current condition, can thus avoiding unnecessary replacements. Also, it provides useful information for root cause(s) diagnoses and prognoses about failure mechanisms.
CBM involves periodic and continuous collection and interpretation of data. Limitations and deficiency in data coverage and quality reduce its effectiveness and accuracy. Incomplete data leads to a situation where the development of degradation cannot be followed until just before failure. Therefore, it is necessary to systematically, document and analyze operating conditions.
The condition and life length of significant components of a maintained system depend on three factors:
- Operating and environmental conditions.
- Maintenance activities.
- The time in use.
The loading modes, operating staff skill, the quality of machinery and quality spare parts (handling, storage) and incorrect installation are other important factors. Each factor uses different sources of data and influences maintenance decisions.
Other sources to improve maintenance decisions are: knowledge systems e.g. failure data obtained from historical records, operational experience, knowledge gained from working context. Analysis methods, e.g. Ishikawa and Pareto diagrams, FMECA and/or fault tree models. Diagnostic and prognostic information concerning operational conditions, manufacturing methods, material, operator training, surroundings, etc. Information about the quality controls program, which provides data about early indications of quality deviation, environmental effects of manufacturing system, etc.